Our goal is to identify the origins of micrographia, a handwriting impairment associated with Parkinson's disease, characterized by a progressive diminution of letter size during writing. Based on previous research experience and the existing literature on Parkinsonian micrographia, several motor control explanations of micrographia are investigated: (a) immobilization of wrist, (b) sequentialization of overlapping movements through the suppression of simultaneous components, (c) impaired coordination between fingers, wrist, and arm, (d) improper scaling of movement amplitude, (e) inaccuracy of force amplitudes, (f) deficient force modulation, and (g) movement hastening. Handwriting movements will be recorded in terms of pen movements in the 2 dimensional plane, and in terms of arm, hand, and finger movements in the 3 dimensional space. Automatized handwriting movement analyses provide the decision criteria to reject or confirm the hypotheses. In order to gain additional validation, the experimental data and the impairments will be simulated using a neural network model of handwriting production, that takes the neural, anatomical, neurophysiological, and biomechanical architecture of the handwriting system into account By combining experimental and neural network paradigms, we hope to unravel the neural causes of micrographia in Parkinson's disease.